This section is intended to introduce the reader to various aspects of art that may be related to various aspects of the present disclosure, which are described and/or claimed below. This discussion is believed to be helpful in providing the reader with background information to facilitate a better understanding of the various aspects of the present disclosure. Accordingly, it should be understood that these statements are to be read in this light, and not as admissions of prior art.
Computer resources hosted in distributed computing (e.g., cloud-computing) environments may be disparately located with different resources potentially having their own functions, properties, and/or permissions. Such resources may include hardware resources (e.g. computing devices, switches, etc.) and software resources (e.g. database applications). These resources may be used to collect and store data at various times related to a variety of measurable properties, including network, hardware, or database performance properties measured at different times. As systems for collecting data become more readily available and the costs for storage hardware continue to decrease, the amount of data that these computer resources are capable of collecting is increasing. For instance, in addition to collecting raw data more frequently, metadata associated with the time in which the raw data has been generated or acquired may also be stored for a given data set.
Although the capabilities of computer resources for collecting and storing more data continues to expand, the vast amount of collected data may prove to be difficult to interpret and synthesize. That is, to draw inferences from the data that may be useful to the operation of the computer resources, the operation of a business, or the like, it may be useful to interpret the data in different manners, based upon particular characteristics of the data. The interpretation may be used to determine a magnitude of likely anomalous data (e.g., an anomalous score for the data), which may be used to report anomalies within the system, enabling enhanced monitoring and sustainment of the system.